| Package | Description |
|---|---|
| opennlp.tools.chunker |
Package related to finding non-recursive syntactic annotation such as noun phrase chunks.
|
| opennlp.tools.doccat |
Package for classifying a document into a category.
|
| opennlp.tools.ml | |
| opennlp.tools.ml.maxent |
Provides main functionality of the maxent package including data structures and
algorithms for parameter estimation.
|
| opennlp.tools.ml.maxent.io |
Provides the I/O functionality of the maxent package including reading
and writting models in several formats.
|
| opennlp.tools.ml.maxent.quasinewton | |
| opennlp.tools.ml.model | |
| opennlp.tools.ml.perceptron | |
| opennlp.tools.namefind |
Package related to finding proper names and numeric amounts.
|
| opennlp.tools.parser |
Package containing common code for performing full syntactic parsing.
|
| opennlp.tools.parser.chunking |
Package containing code for performing full syntactic parsing using shift/reduce-style decisions.
|
| opennlp.tools.postag |
Package related to part-of-speech tagging.
|
| opennlp.tools.sentdetect |
Package related to identifying sentece boundries.
|
| opennlp.tools.tokenize |
Contains classes related to finding token or words in a string.
|
| opennlp.tools.util |
Package containing utility data structures and algorithms used by multiple other packages.
|
| opennlp.tools.util.model |
| Class and Description |
|---|
| AbstractModel |
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Sequence
Class which models a sequence.
|
| SequenceClassificationModel
A classification model that can label an input sequence.
|
| SequenceStream
Interface for streams of sequences used to train sequence models.
|
| Class and Description |
|---|
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Class and Description |
|---|
| DataIndexer
Object which compresses events in memory and performs feature selection.
|
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| SequenceClassificationModel
A classification model that can label an input sequence.
|
| SequenceStream
Interface for streams of sequences used to train sequence models.
|
| Class and Description |
|---|
| AbstractModel |
| Context
Class which associates a real valued parameter or expected value with a particular contextual
predicate or feature.
|
| DataIndexer
Object which compresses events in memory and performs feature selection.
|
| EvalParameters
This class encapsulates the varibales used in producing probabilities from a model
and facilitaes passing these variables to the eval method.
|
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Prior
This interface allows one to implement a prior distribution for use in
maximum entropy model training.
|
| Class and Description |
|---|
| AbstractModel |
| AbstractModelReader |
| AbstractModelWriter |
| ComparablePredicate
A maxent predicate representation which we can use to sort based on the
outcomes.
|
| Context
Class which associates a real valued parameter or expected value with a particular contextual
predicate or feature.
|
| DataReader |
| Class and Description |
|---|
| AbstractModel |
| Context
Class which associates a real valued parameter or expected value with a particular contextual
predicate or feature.
|
| DataIndexer
Object which compresses events in memory and performs feature selection.
|
| MaxentModel
Interface for maximum entropy models.
|
| Class and Description |
|---|
| AbstractDataIndexer
Abstract class for collecting event and context counts used in training.
|
| AbstractModel |
| AbstractModel.ModelType |
| AbstractModelReader |
| AbstractModelWriter |
| ComparableEvent
A maxent event representation which we can use to sort based on the
predicates indexes contained in the events.
|
| ComparablePredicate
A maxent predicate representation which we can use to sort based on the
outcomes.
|
| Context
Class which associates a real valued parameter or expected value with a particular contextual
predicate or feature.
|
| DataIndexer
Object which compresses events in memory and performs feature selection.
|
| DataReader |
| EvalParameters
This class encapsulates the varibales used in producing probabilities from a model
and facilitaes passing these variables to the eval method.
|
| Event
The context of a decision point during training.
|
| FileEventStream
Class for using a file of events as an event stream.
|
| IndexHashTable
The
IndexHashTable is a hash table which maps entries
of an array to their index in the array. |
| MaxentModel
Interface for maximum entropy models.
|
| OnePassDataIndexer
An indexer for maxent model data which handles cutoffs for uncommon
contextual predicates and provides a unique integer index for each of the
predicates.
|
| Prior
This interface allows one to implement a prior distribution for use in
maximum entropy model training.
|
| Sequence
Class which models a sequence.
|
| SequenceStream
Interface for streams of sequences used to train sequence models.
|
| Class and Description |
|---|
| AbstractModel |
| AbstractModelReader |
| AbstractModelWriter |
| ComparablePredicate
A maxent predicate representation which we can use to sort based on the
outcomes.
|
| Context
Class which associates a real valued parameter or expected value with a particular contextual
predicate or feature.
|
| DataIndexer
Object which compresses events in memory and performs feature selection.
|
| DataReader |
| EvalParameters
This class encapsulates the varibales used in producing probabilities from a model
and facilitaes passing these variables to the eval method.
|
| IndexHashTable
The
IndexHashTable is a hash table which maps entries
of an array to their index in the array. |
| MaxentModel
Interface for maximum entropy models.
|
| SequenceStream
Interface for streams of sequences used to train sequence models.
|
| Class and Description |
|---|
| AbstractModel |
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Sequence
Class which models a sequence.
|
| SequenceClassificationModel
A classification model that can label an input sequence.
|
| SequenceStream
Interface for streams of sequences used to train sequence models.
|
| Class and Description |
|---|
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Class and Description |
|---|
| AbstractModel |
| Event
The context of a decision point during training.
|
| Class and Description |
|---|
| AbstractModel |
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Sequence
Class which models a sequence.
|
| SequenceClassificationModel
A classification model that can label an input sequence.
|
| SequenceStream
Interface for streams of sequences used to train sequence models.
|
| Class and Description |
|---|
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Class and Description |
|---|
| AbstractModel |
| Event
The context of a decision point during training.
|
| MaxentModel
Interface for maximum entropy models.
|
| Class and Description |
|---|
| Event
The context of a decision point during training.
|
| Class and Description |
|---|
| AbstractModel |
| MaxentModel
Interface for maximum entropy models.
|
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